def rot90_director(data, axis="+x", out=None):
"""
Rotate a director field by 90 degrees around the specified axis.
Parameters
----------
data: array_like
Array specifying director field with ndim = 4.
axis: str
Axis around which to perform rotation. Can be in the form of
'[s][n]X' where the optional parameter 's' can be "+" or "-" decribing
the sign of rotation. [n] is an integer describing number of rotations
to perform, and 'X' is one of 'x', 'y' 'z', and defines rotation axis.
out : ndarray, optional
Output array.
Returns
-------
y : ndarray
A rotated director field
See Also
--------
data.rotate_director : a general rotation for arbitrary angle.
"""
nz, ny, nx, nv = data.shape
axis_name = axis[-1]
try:
k = int(axis[:-1])
except ValueError:
k = int(axis[:-1] + "1")
angle = np.pi / 2 * k
if axis_name == "x":
r = rotation_matrix_x(angle)
axes = (1, 0)
elif axis_name == "y":
r = rotation_matrix_y(angle)
axes = (0, 2)
elif axis_name == "z":
r = rotation_matrix_z(angle)
axes = (2, 1)
else:
raise ValueError("Unknown axis type {}".format(axis_name))
data_rot = np.rot90(data, k=k, axes=axes) #first rotate data points
return rotate_vector(r, data_rot, out) #rotate vector in each voxel
def rotate_director(rmat,
data,
method="linear",
fill_value=(0., 0., 0.),
norm=True,
out=None):
"""
Rotate a director field around the center of the compute box by a specified
rotation matrix. This rotation is lossy, as datapoints are interpolated.
The shape of the output remains the same.
Parameters
----------
rmat : array_like
A 3x3 rotation matrix.
data: array_like
Array specifying director field with ndim = 4
method : str
Interpolation method "linear" or "nearest"
fill_value : numbers, optional
If provided, the values (length 3 vector) to use for points outside of the
interpolation domain. Defaults to (0.,0.,0.).
norm : bool,
Whether to normalize the length of the director to 1. after rotation
(interpolation) is performed. Because of interpolation error, the length
of the director changes slightly, and this options adds a constant
length constraint to reduce the error.
out : ndarray, optional
Output array.
Returns
-------
y : ndarray
A rotated director field
See Also
--------
data.rot90_director : a lossless rotation by 90 degrees.
"""
from scipy.interpolate import RegularGridInterpolator
verbose_level = DTMMConfig.verbose
if verbose_level > 0:
print("Rotating director.")
out = np.empty_like(data)
nz, ny, nx, nv = data.shape
shape = (nz, ny, nx)
az, ay, ax = [np.arange(-l / 2. + .5, l / 2. + .5) for l in shape]
fillx, filly, fillz = fill_value
xdir = RegularGridInterpolator((az, ay, ax),
data[..., 0],
fill_value=fillx,
bounds_error=False,
method=method)
ydir = RegularGridInterpolator((az, ay, ax),
data[..., 1],
fill_value=filly,
bounds_error=False,
method=method)
zdir = RegularGridInterpolator((az, ay, ax),
data[..., 2],
fill_value=fillz,
bounds_error=False,
method=method)
zz, yy, xx = np.meshgrid(az,
ay,
ax,
indexing="ij",
copy=False,
sparse=True)
out[..., 0] = xx
out[..., 1] = yy
out[..., 2] = zz
out = rotate_vector(rmat.T, out, out) #rotate coordinates
#out2 = out.copy()
#out2[...,0] = out[...,2]
#out2[...,2] = out[...,0]
out2 = out[..., ::-1] #reverse direction instead of copying
#interpolate new director field
xnew = xdir(out2)
ynew = ydir(out2)
znew = zdir(out2)
out[..., 0] = xnew
out[..., 1] = ynew
out[..., 2] = znew
rotate_vector(rmat, out, out) #rotate vector in each voxel
if norm == True:
s = director2order(out)
mask = (s == 0.)
s[mask] = 1.
return np.divide(out, s[..., None], out)
return
size_x = pitch_x * 1
size_z = pitch_z * 2
tilt = np.arctan(pitch_z / pitch_x)
twist = np.arange(
0, 2 * np.pi * size_z / pitch_z, 2 * np.pi / pitch_z)[:, None] + np.arange(
0, 2 * np.pi * size_x / pitch_x, 2 * np.pi / pitch_x)[None, :]
director = np.empty(shape=twist.shape + (3, ))
director[..., 0] = np.cos(twist) #x component
director[..., 1] = np.sin(twist) #y component
director[..., 2] = 0 # z component
r = rotation.rotation_matrix_y(tilt)
director = rotation.rotate_vector(r, director)
epsa = data.director2angles(director)
#: box dimensions
NLAYERS, HEIGHT, WIDTH = twist.shape[0], twist.shape[1], 1
d = np.ones(shape=(NLAYERS, ))
epsv = np.empty(shape=(NLAYERS, HEIGHT, 3), dtype=dtmm.conf.CDTYPE)
epsv[..., 0] = no**2
epsv[..., 1] = no**2
epsv[..., 2] = ne**2
beta, phi, intensity = 0, 0, 1